「review」の検索結果

Review or refactor an existing SKILL.md and its bundled resources — a smaller always-loaded core, conditional references, preserved behavior, lean/guided consumer profiles, and an A/B protocol to compare a candidate with the previous version. Use when a skill repeats itself, loads references on every run, triggers too broadly or misses legitimate requests, or needs its efficiency measured across models. Do NOT use for writing a new skill from scratch, refactoring application code, translating a skill verbatim, or performing the target skill's own task.

日本語の概要は準備中です。原文の説明を表示しています。

Use when an approved plan needs executing task by task in this session, with a fresh implementer per task and review between tasks

日本語の概要は準備中です。原文の説明を表示しています。

Delegate a bounded repository task to an allowlisted external coding CLI through the guarded Flow runner. Use for automatic provider selection or explicit Codex, OpenCode, Kimi, Gemini, or Kiro delegation that requires timeout handling and independent local review.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user wants to execute an existing pwdev-feat action plan — 'executar o plano user-crud', 'exec latest', 'rodar o plano', 'retomar a execução'. Dispatches the executor (subagent when the runtime has one, inline otherwise) in IMPLEMENT or REPORT mode, handles NEEDS_ADVICE with the advisor, and supports --resume. Do NOT use to create plans (feat-feature, feat-backend, feat-frontend, feat-test, feat-review) or for tasks without a plan (feat-quick).

日本語の概要は準備中です。原文の説明を表示しています。

Deliver a small, bounded code change through inspection, a mini-plan, implementation, testing, review, and adversarial verification. Use for bug fixes, configuration changes, and features expected to touch no more than five files.

日本語の概要は準備中です。原文の説明を表示しています。

Analyze a completed phase diff for high-confidence behavior-preserving simplifications and apply only explicitly approved proposals. Use after execution and before review to reduce duplication, dead code, needless complexity, or avoidable inefficiency.

日本語の概要は準備中です。原文の説明を表示しています。

Use when an existing skill must be refactored to cut context and ambiguity without losing behavior, safety or fallbacks — 'refatorar a skill', 'reduzir esta SKILL.md', 'revisar skill com métricas' — with before/after metrics, preserved invariants and three review rounds.

日本語の概要は準備中です。原文の説明を表示しています。

Adversarially verify an implementation against its objective, acceptance criteria, definition of done, and prohibitions using fresh evidence. Use for completion gates, release readiness, or independent verification after implementation and review.

日本語の概要は準備中です。原文の説明を表示しています。

Pesquisa de Voz do Cliente (VOC) antes de escrever qualquer copy — coleta a linguagem literal do público em avaliações, fóruns, redes sociais, tickets de suporte e transcrições de vendas. Use quando o usuário disser "pesquisa de público", "voz do cliente", "VOC", "o que os clientes falam", "pesquisar concorrente", "analisar reviews", "levantar objeções", "não sei o que escrever", ou quando pedir copy sem que exista seção 6 preenchida em .claude/pwdev-copy-context.md. Produz frases verbatim, não paráfrases.

日本語の概要は準備中です。原文の説明を表示しています。

Escreve ou reescreve copy de páginas de marketing — home, landing page, página de preço, de produto, de funcionalidade, institucional. Use quando o usuário disser "escrever copy", "criar landing page", "reescrever essa página", "preciso de headline", "melhorar o CTA", "copy do site", "texto da home". Para e-mail use copy-email; para anúncio use copy-ads; para revisar texto pronto use copy-review.

日本語の概要は準備中です。原文の説明を表示しています。

Revisa e melhora copy existente através de 7 passes focados (clareza, voz, e daí, prove, especificidade, emoção, risco zero) somados à detecção determinística de padrões de escrita de IA. Use quando o usuário disser "revisar copy", "melhorar esse texto", "revisão", "está parecendo IA", "polir", "dar uma olhada nesse texto", "feedback de copy", ou logo após qualquer skill copy-* gerar um rascunho. Não reescreve do zero — aprimora preservando a mensagem central.

日本語の概要は準備中です。原文の説明を表示しています。

Audit a GTK4/libadwaita app for GNOME HIG compliance across 12 categories (text, icons, layout, shortcuts, accessibility, color, dialogs, responsiveness, CSS, GSettings, i18n), then fix violations category by category. Use when asked to audit, review, polish, or "make HIG-compliant" a GNOME app, or before a release/Flathub submission.

日本語の概要は準備中です。原文の説明を表示しています。

Prepare or update a Fabric pull request by proving the changeset-or-skip decision, validation evidence, DCO sign-off, and public-safe PR metadata. Use before the first push, after later revisions, or when asked to create or update a PR. Do not use to review an unrelated PR or authorize relay.

日本語の概要は準備中です。原文の説明を表示しています。

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

日本語の概要は準備中です。原文の説明を表示しています。

Use Neon serverless Postgres with branching, connection pooling, and instant scalability for modern applications with Prisma or Drizzle ORM integration. Use when setting up serverless Postgres databases, implementing database branching for preview environments, configuring connection pooling, optimizing for serverless cold starts, using Prisma with Neon, implementing database migrations, scaling databases automatically, or building applications on Vercel/Netlify with Postgres.

日本語の概要は準備中です。原文の説明を表示しています。

Daily per-section review cycle driving a section toward the smallest, clearest form that still does everything it does today. Selects its section live each run (scripted), inventories every file, derives the target shape before any scan, works parallel reading threads into one ranked list and strikes it on a 2-3h budget. One PR per run; each run's report and Needs-Peter queue live in its own docs/health/runs/ file; 'resume' applies Peter's answers later. Use for the morning section-improvement run, 'doctor <section>', or 'run section doctor'.

日本語の概要は準備中です。原文の説明を表示しています。

Run multiple Reforge-guided section-refactor lanes in parallel, each in its own worktree/branch off origin/main, with a score-blind adversarial review panel gating every commit, one draft PR per section. Use when the user wants to reduce Reforge surface/internal score across several sections at once via architecturally-correct deletions (dead surface, entity-leak removal, cross-section read-splits) — not by relocation, parameter bags, or accessibility-dodging. Wraps the per-lane process in .codex/skills/humans-refactor. Triggers: 'refactor swarm', 'parallel section refactors', 'run reforge refactor on Users/Tickets/...', 'burn down surface score across sections'. Has an intensity dial (light|standard|deep) and a workflow|solo execution mode to trade token burn against autonomy per unit of output.

日本語の概要は準備中です。原文の説明を表示しています。

Check an externally created PR for coding rule violations against memory/INDEX.md atoms and docs/architecture/code-review-rules.md.

日本語の概要は準備中です。原文の説明を表示しています。

When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured data," "JSON-LD," "rich snippets," "schema.org," "FAQ schema," "product schema," "review schema," "breadcrumb schema," "Google rich results," "knowledge panel," "star ratings in search," or "add structured data." Use this whenever someone wants their pages to show enhanced results in Google. For broader SEO issues, see seo-audit. For AI search optimization, see ai-seo.

日本語の概要は準備中です。原文の説明を表示しています。

Manage project learnings. Review, search, prune, and export what gstack has learned across sessions. Use when asked to "what have we learned", "show learnings", "prune stale learnings", or "export learnings". Proactively suggest when the user asks about past patterns or wonders "didn't we fix this before?"

日本語の概要は準備中です。原文の説明を表示しています。

Self-tuning question sensitivity + developer psychographic for gstack (v1: observational). Review which AskUserQuestion prompts fire across gstack skills, set per-question preferences (never-ask / always-ask / ask-only-for-one-way), inspect the dual-track profile (what you declared vs what your behavior suggests), and enable/disable question tuning. Conversational interface — no CLI syntax required. Use when asked to "tune questions", "stop asking me that", "too many questions", "show my profile", "what questions have I been asked", "show my vibe", "developer profile", or "turn off question tuning". (gstack) Proactively suggest when the user says the same gstack question has come up before, or when they explicitly override a recommendation for the Nth time.

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Ship workflow: detect + merge base branch, run tests, review diff, bump VERSION, update CHANGELOG, commit, push, create PR. Use when asked to "ship", "deploy", "push to main", "create a PR", "merge and push", or "get it deployed". Proactively invoke this skill (do NOT push/PR directly) when the user says code is ready, asks about deploying, wants to push code up, or asks to create a PR. (gstack)

日本語の概要は準備中です。原文の説明を表示しています。

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

日本語の概要は準備中です。原文の説明を表示しています。

Render a proposed redesign of a page on the current website as a self-contained static HTML file, then iterate via the impeccable craft loop. Per-page, idempotent, stale-aware. Use when the user asks for a redesign prototype, a before/after comparison, a design preview, a page mockup, a visual diff of the redesign, or invokes /stardust:prototype.

日本語の概要は準備中です。原文の説明を表示しています。